8hG)SSKrSSKrSSKJr SSKJr /SQrSrSrSr \ 4Sjr \ 4S jr \ 4S jr \ 4S jr\ 4S jr\ 4S jr\ 4SjrSr\ 4SjrS\ 4SjrSSjrSrSrSrg)N)Mapping)reduce) merge merge_withvalmapkeymapitemmap valfilter keyfilter itemfilterassocdissocassoc_in update_inget_incURS[5nU(a,[URSUR 5SS35eU$)Nfactoryz'() got an unexpected keyword argument 'r')popdict TypeError__name__popitem)fkwargsrs m/var/www/fran/franai/venv/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py _get_factoryrsMjjD)G zzlA&..BRSTBUAVVW X   Nc[U5S:Xa[US[5(dUSn[[U5nU"5nUHnUR U5 M U$)zMerge a collection of dictionaries >>> merge({1: "one"}, {2: "two"}) {1: 'one', 2: 'two'} Later dictionaries have precedence >>> merge({1: 2, 3: 4}, {3: 3, 4: 4}) {1: 2, 3: 3, 4: 4} See Also: merge_with r)len isinstancerrrupdate)dictsrrrvds rrr"sU 5zQz%(G<<a5&)G B  !  Irc"[U5S:Xa[US[5(dUSn[[U5nU"5nUH;nUR 5H$upgXd;aU/XF'MXFR U5 M& M= [XU5$)aMerge dictionaries and apply function to combined values A key may occur in more than one dict, and all values mapped from the key will be passed to the function as a list, such as func([val1, val2, ...]). >>> merge_with(sum, {1: 1, 2: 2}, {1: 10, 2: 20}) {1: 11, 2: 22} >>> merge_with(first, {1: 1, 2: 2}, {2: 20, 3: 30}) # doctest: +SKIP {1: 1, 2: 2, 3: 30} See Also: merge r r)r!r"rrritemsappendr)funcr$rrresultr&kvs rrr:s 5zQz%(G<<a:v.G YF GGIDAC    #  $ ((rc U"5nUR[UR5[XR 5555 U$)zApply function to values of dictionary >>> bills = {"Alice": [20, 15, 30], "Bob": [10, 35]} >>> valmap(sum, bills) # doctest: +SKIP {'Alice': 65, 'Bob': 45} See Also: keymap itemmap )r#zipkeysmapvaluesr*r&rr%s rrrWs4 BIIc!&&(Chhj123 Irc U"5nUR[[XR55UR 555 U$)zApply function to keys of dictionary >>> bills = {"Alice": [20, 15, 30], "Bob": [10, 35]} >>> keymap(str.lower, bills) # doctest: +SKIP {'alice': [20, 15, 30], 'bob': [10, 35]} See Also: valmap itemmap )r#r/r1r0r2r3s rrrgs4 BIIc#dFFH%qxxz23 IrcdU"5nUR[XR555 U$)zApply function to items of dictionary >>> accountids = {"Alice": 10, "Bob": 20} >>> itemmap(reversed, accountids) # doctest: +SKIP {10: "Alice", 20: "Bob"} See Also: keymap valmap )r#r1r(r3s rr r ws' BIIc$ "# IrclU"5nUR5HupEU"U5(dMXSU'M U$)zFilter items in dictionary by value >>> iseven = lambda x: x % 2 == 0 >>> d = {1: 2, 2: 3, 3: 4, 4: 5} >>> valfilter(iseven, d) {1: 2, 3: 4} See Also: keyfilter itemfilter valmap r( predicater&rr%r,r-s rr r 4 B  Q<<qE IrclU"5nUR5HupEU"U5(dMXSU'M U$)zFilter items in dictionary by key >>> iseven = lambda x: x % 2 == 0 >>> d = {1: 2, 2: 3, 3: 4, 4: 5} >>> keyfilter(iseven, d) {2: 3, 4: 5} See Also: valfilter itemfilter keymap r7r8s rr r r:rcpU"5nUR5HnU"U5(dMUupVXcU'M U$)zFilter items in dictionary by item >>> def isvalid(item): ... k, v = item ... return k % 2 == 0 and v < 4 >>> d = {1: 2, 2: 3, 3: 4, 4: 5} >>> itemfilter(isvalid, d) {2: 3} See Also: keyfilter valfilter itemmap r7)r9r&rr%itemr,r-s rr r s9 B  T??DAqE Irc>U"5nURU5 X$U'U$)zReturn a new dict with new key value pair New dict has d[key] set to value. Does not modify the initial dictionary. >>> assoc({"x": 1}, "x", 2) {'x': 2} >>> assoc({"x": 1}, "y", 3) # doctest: +SKIP {'x': 1, 'y': 3} )r#)r&keyvaluerd2s rr r s" BIIaLsG Irc [[U5nU"5n[U5[U5S-:a%URU5 UH nXT;dM XE M U$[ U5nUR U5 UH nXXG'M U$)aReturn a new dict with the given key(s) removed. New dict has d[key] deleted for each supplied key. Does not modify the initial dictionary. >>> dissoc({"x": 1, "y": 2}, "y") {'x': 1} >>> dissoc({"x": 1, "y": 2}, "y", "x") {} >>> dissoc({"x": 1}, "y") # Ignores missing keys {'x': 1} g333333?)rrr!r#setdifference_update)r&r0rrrAr? remainingr,s rrrs66*G B 4y3q6C< ! CyG I F ##D)ADBE Irc(^[XU4SjTU5$)aReturn a new dict with new, potentially nested, key value pair >>> purchase = { ... "name": "Alice", ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, ... "credit card": "5555-1234-1234-1234", ... } >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP {'credit card': '5555-1234-1234-1234', 'name': 'Alice', 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} c>T$N)xr@s rassoc_in..sr)r)r&r0r@rs ` rrrs Qoug >>rc[U5n[U5nU"5=pxURU5 UH5n X`;aXnU"5n U RU5 OU"5=p U =X'nU nM7 X`;aU"X5X'U$U"U5X'U$)azUpdate value in a (potentially) nested dictionary inputs: d - dictionary on which to operate keys - list or tuple giving the location of the value to be changed in d func - function to operate on that value If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the original dictionary with v replaced by func(v), but does not mutate the original dictionary. If k0 is not a key in d, update_in creates nested dictionaries to the depth specified by the keys, with the innermost value set to func(default). >>> inc = lambda x: x + 1 >>> update_in({"a": 0}, ["a"], inc) {'a': 1} >>> transaction = { ... "name": "Alice", ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, ... "credit card": "5555-1234-1234-1234", ... } >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP {'credit card': '5555-1234-1234-1234', 'name': 'Alice', 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} >>> # updating a value when k0 is not in d >>> update_in({}, [1, 2, 3], str, default="bar") {1: {2: {3: 'bar'}}} >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) {1: 'foo', 2: {3: {4: 1}}} )iternextr#) r&r0r*defaultrksr,r%innerr?dtemps rrrsF dB RABIIaL 6AIE LLO !A  5  v: I= Irc[[RX5$![[[ 4a U(aeUs$f=f)aReturns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless ``no_default`` is specified, then it raises KeyError or IndexError. ``get_in`` is a generalization of ``operator.getitem`` for nested data structures such as dictionaries and lists. >>> transaction = { ... "name": "Alice", ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, ... "credit card": "5555-1234-1234-1234", ... } >>> get_in(["purchase", "items", 0], transaction) 'Apple' >>> get_in(["name"], transaction) 'Alice' >>> get_in(["purchase", "total"], transaction) >>> get_in(["purchase", "items", "apple"], transaction) >>> get_in(["purchase", "items", 10], transaction) >>> get_in(["purchase", "total"], transaction, 0) 0 >>> get_in(["y"], {}, no_default=True) Traceback (most recent call last): ... KeyError: 'y' See Also: itertoolz.get operator.getitem )roperatorgetitemKeyError IndexErrorr)r0collrP no_defaults rrr?s<@h&&33 j) ,  s >>c^[T[5(a7[T5S:Xa TSmU4Sj$T(a[R"T6$S$[R"T5$)Nr rc>UT4$rHrI)rJindexs rrKgetter..ks ah[rcg)NrIrI)rJs rrKr^osRr)r"listr!rU itemgetter)r]s`rgetterrbgsU% u:?!HE( ( &&. . ""5))rc[U5(d [U5n[R"S5nUHnX "U5"U5 M 0nUR 5HupVUR XE'M U$)a*Group a collection by a key function >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] >>> groupby(len, names) # doctest: +SKIP {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} >>> iseven = lambda x: x % 2 == 0 >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} Non-callable keys imply grouping on a member. >>> groupby( ... "gender", ... [ ... {"name": "Alice", "gender": "F"}, ... {"name": "Bob", "gender": "M"}, ... {"name": "Charlie", "gender": "M"}, ... ], ... ) # doctest:+SKIP {'F': [{'gender': 'F', 'name': 'Alice'}], 'M': [{'gender': 'M', 'name': 'Bob'}, {'gender': 'M', 'name': 'Charlie'}]} Not to be confused with ``itertools.groupby`` See Also: countby c/R$rH)r)rIrrrKgroupby..s r)callablerb collections defaultdictr(__self__)r?seqr&r=r%r,r-s rgroupbyrktsh< C==Sk 12A #d) T B   Irc*[[U55$)z6The first element in a sequence >>> first("ABC") 'A' )rOrN)rjs rfirstrms S ?r)NF)rgrUcollections.abcr functoolsr__all__rrrrrrr r r r r rrrrrbrkrmrIrrrqs# "0):!  !  "  %)(%)(&*0"&  :&* ? &*48v%P *&Rr